Novel Urinary Biomarkers For Diagnosing Bipolar Disorder

BackgroundBipolar disorder (BD) is a very common clinical and debilitating mentaldisorder accounted for1%of the population in its incidence. BD, unlikedepression, is sometimes presented as a hypomanic or manic mood, such asunusually good, quick thinking activity and energetic; sometimes presentedas depressive state, such as depressed mood and interest anorgasmia. BD hashigh probability of incidence, recurrence and suicide. As so far, there is noclear conclusion about the pathogenesis of bipolar disorder. Mostresearchers tend to think that BD is caused by the combination of biologicalfactors, heritage factors and psychosocial factors, and the effect of heritagefactors is more prominent.Unlike many other mental diseases, the pathogenesis of bipolar disorderhas not yet been elucidated. There is still no objective indicator or auxiliarylaboratory means for clinicians using to support the clinical findings. SomeScale that clinicians use to “diagnose” BD can only be taken as an adjuncttool to the diagnosis of the disease, but not the exact diagnosis. Hitherto, thediagnosis of bipolar disorder is only dependent on the patient’s own description of the clinical symptoms, adding on testing psychiatricsymptoms, considering the past history of a return visit and the general lawof the development of the disease.ObjectiveQuantitative change of metabolites in the human body is often caused bythe non-normal state of human body, which means get sick. Explore thequantitative change of certain metabolites in the urine that come from thebipolar disorder patients will help us investigate its pathogenesis, andprovide a new perspective for the research and development of the diagnosistool of BD. This work is aimed at finding a group of metabolites to be as adiagnosis tool of BD by comparing normal person with BD patients in thelevel of metabolites in the urine.MethodStep1.collect urine samples from BD patients and normal person.Step2.handle urine samples using centrifugal machine under theparameter of3000round per minute, ten minutes and normal temperature.Step3.preserve urine samples in the minus80degree Celsius refrigeratorafter centrifugating and repackaging.Step4.detect metabolites in urine samples by nuclear magnetic resonancespectroscopy-based metabonomic method.Step5.data analysis using orthogonal partial least-squares discriminantanalysis (OPLS-DA) and logistic regression. The former was performed to find differential metabolites contributing to the separation between BDsubjects and controls; the later was applied to obtain a more practical andhigh accuracy metabolites group.ResultBy statistical analysis of the two sets of urine data, a total of20differentmetabolites have significantly quantitative changes between BD subjectsand controls. Moreover, Four metabolites, including α-hydroxybutyrate,isobutyrate, N-methylnicotinamide and choline, are found to be anacceptable group to discriminate BD subjects and controls. A panel that iscomprised of these metabolites can effectively distinguish BD subjects fromcontrols. The area under the receiver operating characteristic curve (AUC)was0.89in the building set (n=62controls and n=60BD patients).Furthermore, these metabolites panel is capable of discriminating blindedtest samples (n=34controls and n=26BD subjects) with an AUC of0.86.ConclusionThis work obtains a preliminary objective indicator, which consists ofthese four metabolites, to help the diagnosis of bipolar disorder. Moreover,our work can be helpful in the subsequently further studying of pathogenesisof bipolar disorder, and provide a new perspective for proteomics.